The combination of smooth servo control and local shape reconstruction was later used for full object reconstruction (Fig. REF , middle row), which remains an problem under active investigation in the field [1]}, [2]}. Our approach improves upon related work [3]}, [4]} that instead trained insensitivity to shear into the prediction network itself. An obvious drawback of this approach, even though it works well for smooth servo control, is that it does not extend readily to predict other tactile dimensions such as parameters of the local contact geometry. In that case, new labelled data would need collecting to train a new model for each intended task. Our approach, of shear removal from tactile images, instead means that a single model based on the canonical (tapping) data can be re-used.
